Practical object recognition problems often have to be solved under severe computation and time constraints. Some examples of interest are natural user interfaces, automotive active safety, robotic vision or sensing for the Internet of Things (IoT). Often the problem is to obtain high accuracy in real time, on a low power platform, or in a background process that may only utilize a small fraction of the central processing unit (CPU). In other cases the classifier is part of a cascade, or a complex multiple-classifier system. Various architectures have been suggested and/or used to optimize the accuracy-speed trade-off.